Jobs at YipitData

The Account Development Manager will manage client relationships, drive client engagement, execute growth strategies, and develop commercial strategies for renewals and upsells.

As a Software Engineer, you'll build tools, improve APIs, manage QA infrastructure, grasp business needs, and ensure system scalability.

The Senior Recruiter will lead high-impact recruiting efforts for the GTM organization, focusing on strategic searches across Sales, Marketing, Customer Success, and Strategy. Responsibilities include managing the full recruiting cycle, developing talent pipelines, enhancing candidate experience, and utilizing ATS systems effectively.

The Senior Recruiter will manage full-cycle recruiting focused on senior leadership roles, develop talent pipelines, and enhance candidate experience while utilizing metrics for continuous improvement.

The Client Strategy Manager will manage client relationships, develop commercial strategies, and ensure client success through proactive engagement and support. This role includes account management, upselling, and enhancing client engagement with the firm's analytics services.

The Associate Director, Solutions will lead a client-facing team at YipitData, responsible for delivering bespoke analysis and data products, managing client experiences, and leveraging AI for operational efficiency.

The Revenue Operations Associate will support revenue growth by implementing processes, analyzing sales data, and enhancing workflows across Sales, Marketing, and Client Success teams.

The Senior QA Engineer will develop test plans, handle automated and performance testing, manage defects, and collaborate with teams for project progress.

As a QA Software Engineer, you will ensure product quality by designing tests, conducting regression testing, identifying bugs, and collaborating with teams to enhance software stability.

Design end-to-end UX for an AI-powered B2B data product. Translate complex AI and data concepts into intuitive, trustworthy interfaces; conduct user research; define workflows; collaborate with Product, Engineering, and Data Science; contribute to design systems and maintain design quality through launches.

Own the conversion of raw alternative datasets into scalable, AI-ready data products. Define methodologies, metric definitions, and guardrails for AI-driven insights. Partner with engineering, product, and customers to expand use cases, ensure data quality, validate changes, and manage incidents to deliver reliable, explainable data products at scale.

Own and deliver high-impact retail data products by designing and running QA, investigating and resolving complex data quality issues, improving classification and attribution, collaborating with Insights and Engineering to automate and streamline pipelines, and communicating methodology and limitations to clients and stakeholders.

Lead a global, hands-on data engineering team building large-scale Databricks/PySpark pipelines, production datasets, customer-facing data feeds, AI-ready analytical datasets, and data quality/observability systems. Partner cross-functionally, use AI coding tools to accelerate delivery, and ensure operational excellence, reliability, and documentation for investor-facing products.

Own day-to-day facilities and workplace experience for the Austin office: manage vendors and budgets, plan space and office projects, ensure health/safety compliance, improve operational processes and tools, support events and onboarding logistics, and track workplace KPIs to present recommendations to leadership.

The Product Manager will define and scale a quant platform for alternative datasets, collaborate with teams to develop product specifications, conduct customer research, and manage go-to-market strategies.

Identify and engage investor prospects across Asia Pacific via outbound and inbound channels, qualify leads, map buyer personas at hedge funds and investment managers, collaborate with sales, marketing, and product teams, and use sales tools to book qualified opportunities and drive pipeline.

The Data Product Analyst will own Signals data products, work with AI and Data Engineering, ensure data quality, conduct analyses, and shape product improvements through client feedback.

The Data Operations Analyst develops custom product attribution based on client needs, utilizing tagging and machine learning; ensuring data mapping accuracy and project delivery.

The Senior Software Engineer will architect and develop key features for YipitData's AI Platform, ensuring robust application performance and collaborating with teams to enhance product reliability.

As a Tech Lead, you will own the technical direction of a B2B analytics platform, lead engineering teams, and ensure production reliability while collaborating with various stakeholders to translate business needs into technical solutions.